Method of analyzing surface modification of a specimen in a charged-particle microscope

ABSTRACT

A method of investigating a specimen using a charged particle microscope, including:
         Producing and storing a first image, of a first, initial surface of the specimen;   In a primary modification step, modifying said first surface, thereby yielding a second, modified surface;   Producing and storing a second image, of said second surface;   Using a mathematical Image Similarity Metric to perform pixel-wise comparison of said second and first images, so as to generate a primary figure of merit for said primary modification step.

The invention relates to a method of investigating a specimen using:

-   -   A charged-particle microscope comprising:        -   A specimen holder, for holding the specimen;        -   A source, for producing a beam of charged-particle            radiation;        -   An illuminator, for directing said beam so as to irradiate a            surface of the specimen;        -   An imaging detector, for receiving a flux of radiation            emanating from the specimen in response to said irradiation,            so as to produce an image of at least part of said surface;    -   An apparatus that can be invoked to modify said surface by        performing thereon a process chosen from the group comprising        material removal, material deposition, and combinations hereof.

The invention also relates to a charged-particle microscope that can beused in performing such a method.

Charged-particle microscopy is a well-known and increasingly importanttechnique for imaging microscopic objects, particularly in the form ofelectron microscopy. Historically, the basic genus of electronmicroscope has undergone evolution into a number of well-knownmicroscope species, such as the Transmission Electron Microscope (TEM),Scanning Electron Microscope (SEM), and Scanning Transmission ElectronMicroscope (STEM), and also into various sub-species, such as so-called“dual-beam” tools (e.g. a FIB-SEM), which additionally employ a“machining” Focused Ion Beam (FIB), allowing supportive activities suchas ion-beam milling or Ion-Beam-Induced Deposition (IBID), for example.More specifically:

-   -   In a SEM, irradiation of a specimen by a scanning electron beam        precipitates emanation of “auxiliary” radiation from the        specimen, in the form of secondary electrons, backscattered        electrons, X-rays and photoluminescence (infrared, visible        and/or ultraviolet photons), for example; one or more components        of this emanating radiation is/are then detected and used for        image accumulation purposes, and/or spectroscopic analysis (as        in the case of EDX (Energy-Dispersive X-Ray Spectroscopy), for        example).    -   In a TEM, the electron beam used to irradiate the specimen is        chosen to be of a high-enough energy to penetrate the specimen        (which, to this end, will generally be thinner than in the case        of a SEM specimen); the flux of transmitted electrons emanating        from the specimen can then be used to create an image, or        produce a spectrum (as in the case of EELS, for example;        EELS=Electron Energy-Loss Spectroscopy). If such a TEM is        operated in scanning mode (thus becoming a STEM), the        image/spectrum in question will be accumulated during a scanning        motion of the irradiating electron beam.        More information on some of the topics elucidated here can, for        example, be gleaned from the following Wikipedia links:    -   en.wikipedia.org/wiki/Electron_microscope    -   en.wikipedia.org/wiki/Scanning_electron_microscope    -   en.wikipedia.org/wiki/Transmission_electron_microscopy    -   en.wikipedia.org/wiki/Scanning_transmission_electron_microscopy        As an alternative to the use of electrons as irradiating beam,        charged-particle microscopy can also be performed using other        species of charged particle. In this respect, the phrase        “charged particle” should be broadly interpreted as encompassing        electrons, positive ions (e.g. Ga or He ions), negative ions,        protons and positrons, for instance. As regards ion-based        microscopy, some further information can, for example, be        gleaned from sources such as the following:    -   en.wikipedia.org/wiki/Scanning_Helium_Ion_Microscope    -   W. H. Escovitz, T. R. Fox and R. Levi-Setti, Scanning        Transmission Ion Microscope with a Field Ion Source, Proc. Nat.        Acad. Sci. USA 72(5), pp 1826-1828 (1975).    -   www.innovationmagazine.com/innovation/volumes/v7n1/coverstory3.shtml        It should be noted that, in addition to imaging and/or        spectroscopy, a charged-particle microscope (CPM) may also have        other functionalities, such as examining diffractograms,        performing (localized) surface modification (e.g. milling,        etching, deposition), etc.

In all cases, a Charged-Particle Microscope (CPM) will comprise at leastthe following components:

-   -   A radiation source, such as a Schottky electron source or ion        gun.    -   An illuminator, which serves to manipulate a “raw” radiation        beam from the source and perform upon it certain operations such        as focusing, aberration mitigation, cropping (with a        stop/iris/condensing aperture), filtering, etc. It will        generally comprise one or more charged-particle lenses, and may        comprise other types of particle-optical component also. If        desired, the illuminator can be provided with a deflector system        that can be invoked to cause its output beam to perform a        scanning motion across the specimen being investigated.    -   A specimen holder, on which a specimen under investigation can        be held and positioned (e.g. tilted, rotated). If desired, this        holder can be moved so as to effect a scanning motion of the        beam w.r.t. the specimen. In general, such a specimen holder        will be connected to a positioning system such as a mechanical        stage.    -   A detector, which may be unitary or compound/distributed in        nature, and which can take many different forms, depending on        the radiation/entity being recorded. Such a detector may, for        example, be used to register an intensity value, to capture an        image, or to record a spectrum. Examples include        photomultipliers (including solid-state photomultipliers,        SSPMs), photodiodes, (pixelated) CMOS detectors, (pixelated) CCD        detectors, photovoltaic cells, etc., which may, for example, be        used in conjunction with a scintillator film, for instance. For        X-ray detection, use is typically made of a so-called Silicon        Drift Detector (SDD), or a Silicon Lithium (Si(Li)) detector,        for example. Typically, a CPM will comprise several detectors,        of various types.        In the case of a transmission-type CPM (such as a (S)TEM), use        will also be made of:    -   An imaging system, which essentially takes charged particles        that are transmitted through a specimen (plane) and directs        (focuses) them onto analysis/sensing equipment, such as a        detection/imaging device, spectroscopic unit, etc. As with the        illuminator referred to above, the imaging system may also        perform other functions, such as aberration mitigation,        cropping, filtering, etc., and it will generally comprise one or        more charged-particle lenses and/or other types of        particle-optical components.        In what follows, the invention may—by way of example—sometimes        be set forth in the specific context of electron microscopy.        However, such simplification is intended solely for        clarity/illustrative purposes, and should not be interpreted as        limiting.

There are many instances of methods as set forth in the openingparagraph above, in which surface modification is performed with the aidof an apparatus/module that can be located ex situ (outside the CPM) orin situ (within the CPM). Examples of such surface modification includethe following:

-   -   (i) A mechanical cutting tool (subtractive/material removal        process):    -   Here, a contact tool such as a microtome, diamond scoring tool,        obsidian blade, mill or lathe is used (in one or more runs) to        cut/shave/pear a slice of material from (part of) the specimen        surface.    -   (ii) Focused Particle Beam milling (subtractive/material removal        process):    -   Here, a focused particle beam (e.g. an ion or electron beam) of        a chosen energy/size can be scanned across (part of) the        specimen surface so as to ablate material therefrom. If desired,        this procedure can be repeated in successive iterations, so as        to remove successively greater thicknesses of material. The        procedure lends itself to patterned material removal, if        desired.    -   (iii) Etching apparatus (subtractive/material removal process):    -   In this case, a chemical reagent (such as gas-phase etchant) is        used to remove material from the specimen surface. If desired,        this process can be activated/catalyzed using a focused particle        beam, which allows the process to be made highly        localized/patterned, if required. Examples of such an approach        include IBIE (Ion-Beam-Induced Etching) and EBIE        (Electron-Beam-Induced Etching).    -   (iv) Beam-Induced Deposition (additive/material deposition        process):    -   Examples here include IBID (Ion-Beam-Induced Deposition) and        EBID (Electron-Beam-Induced Deposition), in which a focused beam        is used to (locally) instigate/precipitate deposition of        material from a cloud of precursor gas.    -   (v) Physical Vapor Deposition (PVD) (additive/material        deposition process):    -   Examples include sputtering and Molecular Beam Epitaxy (MBE),        for instance.    -   (vi) Chemical Vapor Deposition (CVD) (additive/material        deposition process):    -   Specific examples include PCVD (Plasma-assisted CVD) and MOCVD        (Metal-Organic CVD), for instance.        Techniques (i)-(iv) can (but don't necessarily have to) be        performed using in situ modules in CPMs; technique (i), for        example, can also be performed ex situ, as in the case of the        so-called ATLUM tool (Automated Tape-collecting Lathe        UltraMicrotome), as set forth, for example, in the following        link:    -   cbs.fas.harvard.edu/science/connectome-project/atlum        Techniques (v) and (vi) are conventionally performed ex situ,        but, in principle, could also be performed using an in situ        module.        Specific ways in which to employ surface modification techniques        in CPMs are, for example, set forth in the following documents:    -   U.S. Pat. No. 8,232,523, in which physical slicing (e.g. with a        microtome) is combined with computational image reconstruction        so as to increase the depth range of the reconstruction;    -   EP 2824445 A1, in which various surface modification techniques        are used to improve the Raman spectroscopy signal from a region        of interest on a specimen.

A problem with such methods is that, since the CPM in which thesurface-modified specimen is imaged will typically have nanometer orsub-nanometer resolution, and since the specimen in question will oftenbe very delicate/brittle (e.g. because it is extremely thin (as in thecase of a TEM specimen) or because it has been vitrified, for instance),the employed surface modification technique will have to be performedvery accurately if it is to produce satisfactory results (e.g.qualitatively, quantitatively, and in terms of yield/throughput in thecontext of possible re-runs, touch-ups, sample damage, etc.). To date,there is no accurate way of monitoring such operations: instead, theytend to be rather hit-and-miss and haphazard in nature, and to relyheavily on previous experience/skill of the person performing thespecimen investigation, and also to a certain extent on luck.

It is an object of the invention to address these issues. Morespecifically, it is an object of the invention to provide a way in whichsurface modification techniques as referred to above can be monitored.In particular, it is an object of the invention that such monitoringshould enable relatively fast identification of a failed or corruptedsurface modification attempt. In addition, it is an object of theinvention to provide a monitoring technique that can potentially produceboth qualitative and quantitative output.

These and other objects are achieved in a method as set forth in theopening paragraph above, which method is characterized by the followingsteps:

-   -   Producing and storing a first image, of a first, initial surface        of the specimen;    -   In a primary modification step, invoking said apparatus so as to        modify said first surface, thereby yielding a second, modified        surface;    -   Producing and storing a second image, of said second surface;    -   Using a mathematical Image Similarity Metric (ISM) to perform        pixel-wise comparison of said second and first (CPM) images, so        as to generate a primary Figure Of Merit (FOM) for said primary        modification step.

The current invention makes use of the fact that, aftersurface-modification, the specimen is transferred to a device (CPM) withimaging capability. It also makes use of the fact that a mathematicalISM can be used as a basis to perform automatic pixel-wise comparison ofimages using several objectively definable criteria, on the basis ofwhich one can generate a FOM or “score” (e.g. based on a degree ofcorrelation) that is a quantifier of the similarity (or dissimilarity)of the images in question; in so doing, the ISM treats (and preserves)the images as mathematical fields that are compared in acoordinate-by-coordinate (pixel-by-pixel) manner, thereby allowing(inter-image/intra-image) shape change detection and quantification thatwould not be possible if one were to perform a field-destroying(scalarizing) operation on the images, such as summing or integration,for example. Consequently, when such an ISM is performed on “before” and“after” images (abovementioned first and second images, respectively)pertaining to a given surface modification attempt, it can be used to(autonomously) determine what effect (if any) said attempt had on thesurface in question. For example:

-   -   (a) If a FOM arising from comparison of said “before” and        “after” images has a value above a pre-defined upper threshold,        then one can adjudge that the surface modification attempt in        question has failed/missed (e.g. because of poor        alignment/calibration, process failure (such as a blocked gas        conduit, beam misfire, etc.), failed synchronization, etc.).        Considering a specific instance in which the employed ISM is the        so-called Structural Similarity Index Metric (SSIM), then an        upper-limit FOM-value (e.g. at or very near +1) could be        interpreted in this way.    -   (b) Conversely, if a FOM arising from comparison of said        “before” and “after” images is below a pre-defined lower        threshold, then one can adjudge that the surface modification        attempt in question has corrupted the surface in some way, e.g.        by leaving debris thereon, or causing unintended mechanical        damage thereto. Again considering the specific instance of the        abovementioned SSIM, a lower-limit FOM-value (e.g. at or very        near −1 or 0, depending on the employed SSIM        definition/normalization) could be interpreted in this way.    -   (c) Between these two extremes, one can define an ideal “FOM        band” corresponding to optimal performance of the surface        modification technique. If the FOM lies outside this band (but        within the lower and upper threshold values referred to above),        then one can conclude that the surface modification attempt has        been partially successful, but sub-optimal.        In situations (a) and (c), one could, for example, consider        trying another surface modification attempt with adjusted        parameters (such as cutting tool/beam position, assistive gas        pressure, duration of procedure, etc.); if required, this could        be done in successive iterations, ultimately converging toward a        goal FOM value. In situation (b), one could consider        cleaning/reconditioning the specimen surface before proceeding        with further activities; if required, this process could also be        done in successive steps/iterations, ultimately converging        toward a goal FOM value. From these examples, it is seen that        the invention provides a useful monitor on a procedure that is        otherwise notoriously obscure.

As regards the actual ISM used in the present invention, there arevarious possibilities. One of these—the SSIM—has already been alluded toabove, and produces a FOM value F_(SSIM)(A, B) for the similaritybetween two square (N×N) image “tiles” A and B-taken from corresponding(coordinate) positions of respective first and second images—accordingto the relationship:

${F_{SSIM}\left( {A,B} \right)} = \frac{\left( {{2\mu_{A}\mu_{B}} + C_{1}} \right)\left( {{2\sigma_{AB}} + C_{2}} \right)}{\left( {\mu_{A}^{2} + \mu_{B}^{2} + C_{1}} \right)\left( {\sigma_{A}^{2} + \sigma_{B}^{2} + C_{2}} \right)}$in which:

-   -   μ_(A) is the average of/over A;    -   μ_(B) is the average of/over B;    -   σ_(A) ² is the variance in/of A;    -   σ_(B) ² is the variance in/of B;    -   σ_(AB) is the covariance of A and B;    -   C₁=k₁L² and C₂=k₂L² are “smoothing” variables that prevent        “runaway” in the case of small denominator values, where:        -   L is the dynamic range of the pixel values in A and B;            typically, L=2^(n)−1, where n is the number of bits per            pixel;        -   k₁ and k₂ are set to conventional values of 0.01 and 0.03,            respectively.            This value is typically calculated only for luma (not            chrominance), and will yield a number (FOM) whose magnitude            range depends on the employed normalization but is            conventionally located between an upper-limit value of +1            (exact image match) and a lower-limit value of either −1 or            0 (total image mismatch).            On a related note, one can also define a “dissimilarity”            SSIM (DSSIM), e.g. on the basis of a definition such as:

${F_{DSSIM}\left( {A,B} \right)} = \frac{1 - {F_{SSIM}\left( {A,B} \right)}}{N}$where N is a normalizing factor, e.g. N=2. Such a metric can also beused in the current invention, if so desired.

The current invention is not limited to the use of the abovementionedSSIM, and one can elect to use other ISMs, if desired. Other examples ofISMs include, for instance:

-   -   Mean Squared Error (MSE), which is defined as follows:

${F_{MSE}\left( {A,B} \right)} = {\frac{1}{mn}{\sum\limits_{i = 0}^{m - 1}{\sum\limits_{j = 0}^{n - 1}\left\lbrack {{A\left( {i,j} \right)} - {B\left( {i,j} \right)}} \right\rbrack^{2}}}}$

-   -   for two m×n monochrome images A and B (or image portions at        corresponding coordinates). This will conventionally yield a        number (FOM) with a value that is dependent on the image pixel        value normalization; for example:        -   For image pixel values in the range 0-1, F_(MSE) will also            lie in the range 0-1, with 0 corresponding to exact image            match and 1 corresponding to total image mismatch;        -   For image pixel values in the range 0-255, F_(MSE) will lie            in the range 0-255², with 0 corresponding to exact image            match and 255² corresponding to total image mismatch.    -   Peak Signal-to-Noise Ratio (PSNR), which is defined as follows:

$F_{PSNR} = {10\log_{10}\frac{P_{{MA}\; X}^{2}}{F_{MSE}}}$

-   -   where F_(MSE) is as set forth in the previous item, and P_(MAX)        is the maximum possible pixel value in the images in question;        for example:        -   P_(MAX) has a value of 255 for pixels represented using 8            bits per sample;        -   P_(MAX) has a more generic value of 2^(N)−1 for pixels            represented using N bits per sample.    -   An advantage of PSNR is that its value is (ultimately)        independent of the image pixel value range.    -   Mutual Information of Regions (MIR), which is defined as        follows:

${F_{MIR}\left( {A,B} \right)} = {\sum\limits_{a \in A}^{\;}{\sum\limits_{b \in B}^{\;}{{p\left( {a,b} \right)}{\log\left( \frac{p\left( {a,b} \right)}{{p(a)}{p(b)}} \right)}}}}$

-   -   where:        -   p(a, b) is the joint probability distribution function of A            and B;        -   p(a), p(b) are the marginal probability distribution            functions of A and B, respectively.    -   This can be normalized in such a way that, for example, it will        yield a value of 0 for total image mismatch, and a value of 1        for exact image match.        More information on the mathematics of image comparison (as        applied in other disciplines) can, for example, be gleaned from        the publication by A. A. Goshtasby, Image registration, Advances        in Computer Vision and Pattern Recognition, Chapter 2,        Springer-Verlag, London (2012) [DOI        10.1007/978-1-4471-2458-0_2]. It should be explicitly noted that        mathematical ISMs as used in the present invention are of an        intrinsically different nature to, for example, emission yield        measures and other such scalarizing measures; for instance, if a        feature of a fixed area changes position and/or shape within an        image field, then a mathematical ISM will register this change,        whereas a scalarizing measure will not. More specifically:    -   The mathematical ISM of the present invention compares two        distributions on a member-by-member basis, and distills a metric        value from that comparison (multivariate approach);    -   A scalarizing measure first converts each distribution into a        number (thereby destroying certain specifics of each        distribution), and then compares the two numbers in question.        Scalarizing measures are often used for end-point detection in        etching, whereby a marked brightness change (e.g. corresponding        to cumulative secondary electron yield) coincides with        (complete) removal of a given (e.g. relatively high-brightness)        material from an underlying (e.g. relatively low-brightness)        substrate; to this end, a relatively bright marker material        (such as gold) may be deliberately introduced to a given depth        in a specimen, to act as an imaging “beacon” that will quench        (and thus influence the integrated yield) when it is etched        away.

As set forth above, if a non-acceptable FOM value is obtained inaforementioned cases (a) or (c), then one can repeat the surfacemodification procedure in the hope of obtaining a better FOM value. Thiscan be done “blindly” (in a “hit-and miss” manner); however, in aparticular embodiment of the present invention, it is instead done“intelligently” (in a “steered” manner). In this latter case, theprimary figure of merit (arising from the primary modification step) isused to adjust at least one parameter of a secondary modification step,performed on the (newly created) second surface. In other words, theprimary FOM (or some derivative/hybrid thereof) is used as input to afeedback loop in which one or more parameters of the surfacemodification procedure are (continually) fine-tuned so as to speed upconvergence to an acceptable final FOM value. Examples of suchparameters are, for example:

-   -   The thickness-setting for a mechanical cutting tool;    -   The beam energy and/or scan speed (dwelling time per position)        for a focused particle beam milling tool;    -   The etchant temperature/pressure/flow rate and/or etch time for        a chemical etching tool;    -   The precursor gas pressure/flow rate and/or beam        energy/scan-speed for a beam-induced deposition tool;    -   The deposition speed (e.g. sputter rate or evaporation        temperature) and/or deposition time for a PVD tool;    -   The precursor gas pressure/flow rate and/or deposition time for        a CVD tool.        If it is known (or suspected) that a particular parameter        linearly influences the thickness of material removed from/added        to a surface, then such adjustment might (for example) be        (partially) governed by a relationship of the following form:        Parameter_new=Parameter_old×(1−FOM_present/FOM_ideal)        or a hybrid/derivative hereof.

In another (somewhat related) embodiment of the invention, said primaryfigure of merit is used to quantify a thickness change produced in saidspecimen by said primary modification step. This can, for example bedone on the basis of one or more of:

-   -   Prior calibration(s);    -   A physical model of how the FOM varies as a function of        thickness change;    -   Extrapolation/interpolation on the basis of previously obtained        data pairs,        etc. Quantifying the (subtractive or additive) thickness change        in this way allows a more exact assessment of the nature/extent        of further thickness change required, as well as allowing        correction/fine tuning of the surface modification process        itself.

The invention will now be elucidated in more detail on the basis ofexemplary embodiments and the accompanying schematic drawings, in which:

FIG. 1 renders a longitudinal cross-sectional elevation of a particulartype of CPM in which an embodiment of the current invention can becarried out.

FIG. 2A graphically depicts an ISM FOM value—calculated according to theinvention—for multiple iterations of a surface modification techniqueperformed on a mouse brain specimen.

FIG. 2B shows a nominal image of an exposed surface of the mouse brainspecimen used in generating FIG. 2A.

FIGS. 3A and 3B show images of situations in which one of the surfacemodification iterations of FIG. 2A caused corruption/contamination ofthe specimen surface, resulting in an out-of-spec FOM value.

FIGS. 4A-4C reveal an acquisition error associated with one of thesurface modification iterations of FIG. 2A, resulting in a flagged FOMvalue.

FIGS. 5A-5C reveal an imaging error associated with one of the surfacemodification iterations of FIG. 2A, resulting in a flagged FOM value.

EMBODIMENT 1

FIG. 1 is a highly schematic depiction of an embodiment of a CPM thatlends itself to use in conjunction with the present invention; morespecifically, it shows an embodiment of a scanning-type microscope M,which, in this case, is a SEM (though, in the context of the currentinvention, it could just as validly be an ion-based microscope, forexample, or a TEM, for instance). The microscope M comprises aparticle-optical column/illuminator 1, which produces a beam C of inputcharged particles (in this case, an electron beam) that propagates alonga particle-optical axis C′. The particle-optical column 1 is mounted ona vacuum chamber V, which comprises a specimen holder H and associatedstage/actuator A for holding/positioning a specimen S. The vacuumchamber V is evacuated using vacuum pumps (not depicted). With the aidof voltage source 17, the specimen holder H, or at least the specimen S,may, if desired, be biased (floated) to an electrical potential withrespect to ground.

The particle-optical column 1 comprises an electron source 9 (such as aSchottky emitter), (electrostatic/magnetic) lenses 11, 13 (in general,more complex in structure than the schematic depiction here) to focusthe electron beam C onto the specimen S, and a deflection unit F toperform beam deflection/scanning of the beam C. When the beam C impingeson/is scanned across the specimen S, it will precipitate emission ofvarious types of “stimulated” radiation, such as backscatteredelectrons, secondary electrons, X-rays and cathodoluminescence(infra-red, visible and/or ultra-violet photons); one or more of theseradiation types can then be sensed/recorded using one or more detectors,which may form an image, spectrum, diffractogram, etc., typically byassembling a “map” (or “matrix”) of detector output as a function ofscan position on the specimen. The present Figure shows two suchdetectors, D, D′, which may, for example, be embodied as follows:

-   -   Detector D may, for example, be an electron detector (such as an        SSPM), X-ray detector (such as an SDD or Si(Li) sensor) or a        light detector (such as a photodiode).    -   Detector D′ is a segmented electron detector, comprising a        plurality of independent detection segments (e.g. quadrants)        disposed about a central aperture 15 (allowing passage of the        beam C). Such a detector can, for example, be used to        investigate (the angular dependence of) a flux of output        (secondary or backscattered) electrons emerging from the        specimen S.        These are just examples, and the skilled artisan will understand        that other detector types, numbers and geometries/configurations        are possible.

The microscope M further comprises a controller/computer processing unitE for controlling inter alia the deflection unit F, lenses 11 and 13,and detectors D, D′, and displaying information gathered from thedetectors D, D′ on a display unit 19 (such as a flat panel display);such control occurs via control lines (buses) E′. The controller E (oranother controller) can additionally be used to perform variousmathematical processing, such as combining, integrating, subtracting,false colouring, edge enhancing, and other processing known to theskilled artisan. In addition, automated recognition processes (e.g. asused for particle analysis) may be included in such processing.

In the context of the current invention, the microscope M also comprisesin situ surface modification apparatus, which can be invoked to modify apresented (top) surface of the specimen S by performing thereon aprocess such as material removal, material deposition, etc. As alreadyindicated above, such apparatus can take many different forms, and onlya few possibilities (out of many) are shown in the present Figure. Moreparticularly:

-   -   Item 3 is, for example, an in situ mechanical cutting tool, such        as a (retractable) microtome, knife or mill. Alternatively, it        might be an in situ deposition station, e.g. for performing PVD        or CVD, or an etching unit. When desired, the specimen holder H        can be moved by actuator A so as to “visit” item 3 for        performance of controlled surface modification on specimen S.    -   Item 5 is a secondary particle-optical column, which in the        current case is an ion column, for example. It has an associated        secondary particle-optical axis 5′, which typically intersects        axis C′ within a plane of specimen S. It can, for example, be        used to perform ion milling on specimen S. Alternatively, in        combination with gas admission conduit 7 (which can be used to        admit a controllable flow of a particular precursor gas), it can        be used to perform IBID or IBIE. One could also, of course,        reverse the roles/natures of items 1 and 5, using an ion column        for imaging and an electron column for performing EBID or EBIE,        for example.        In practice, only one of items 3, 5 might be present.        Alternatively, there might be even more of such surface        modification modules present. Moreover, as set forth above, use        could also be made of one or more ex situ surface modification        devices/tools, located outside the chamber/enclosure V. Such        considerations are matters of choice, available space, desired        versatility, etc.

When surface modification is performed on specimen S (e.g. using item 3and/or 5), its ultimate goal will be to remove or add a desired layerthickness from/to an initial surface of the specimen S. In practice,however, it may fail to (satisfactorily) achieve this purpose, andinstead remove/add too little or too much material, and/ordamage/corrupt the specimen surface, e.g. by producingdebris/contamination thereon. In certain instances, such situationswill—to some (limited) extent—qualitatively manifest themselves when thespecimen S is returned to its inspection position under particle-column1, allowing the newly produced specimen surface to be imaged (andvisually inspected by a microscope operator) or otherwise studied (e.g.via a spectrum and/or diffractogram). However, a quantitative inspectionroutine would be much more valuable—particularly one that could beperformed (semi-)automatically. The current invention provides suchquantitative information, in that it uses (autonomous) mathematicalcomparison of “before” and “after” imagery to produce a meaningfulnumerical “score” or “grade” (FOM) for the surface modification steplast performed on the specimen. As explained above, this score value canthen be used to (autonomously) make a decision as to whether or not saidsurface modification was acceptable and—if it wasn't—can be used as abasis to (autonomously) perform/tailor follow-on surface modificationiterations. Such calculations, analysis and control can be performed by(software/firmware running in) processor E or another (dedicated)processor unit.

EMBODIMENT 2

FIG. 2A graphically depicts an ISM FOM value—calculated according to thepresent invention—for multiple iterations of a surface modificationtechnique performed on a mouse brain specimen. In this particular case,a microtome was used to repeatedly shave a given film thickness d_(S)off of the specimen, whereby:

-   -   In one set of iterations, d_(S)=10 nm (dashed line in FIG. 2A);    -   In another set of iterations, d_(S)=20 nm (solid line in FIG.        2A).        An image of the freshly modified surface of the specimen was        taken after each iteration and, according to the invention, an        ISM FOM value was calculated for each corresponding pair of        “before” and “after” images pertaining to each iteration (the        “before” image being the image taken after the preceding        iteration). More particularly, in the current case, each image        was divided into 2048×2048 “pixels” or “tiles” and        F_(SSIM)(A, B) was calculated according to the formula given        above. This value (F) was then plotted against iteration        index (I) to yield FIG. 2A, whereby the vertical axis (F value)        is subdivided into ten “decades” or “bands”, each with a        height/extent of 0.1. From an inspection of FIG. 2A, the        following is evident:    -   For 10 nm cuts (dashed line), the F value is very often in the        uppermost band (0.9-1), and only relatively occasionally outside        it (a notable exception (spike) being at index 80, which will be        discussed in more detail below with respect to FIGS. 4A-4C).        This indicates that, in many cases, the surface modification is        failing to remove material from the specimen (F equal, or very        close, to 1).    -   For 20 nm cuts (solid line), there are still some data points in        the uppermost band (0.9-1), but most are now in a “nominal” band        such as 0.6-0.7/0.7-0.8. Notable exceptions (spikes) occur at        the following indices:        -   48 and 83, which will be discussed in more detail below with            respect to FIGS. 3A, 3B;        -   64, which will be discussed in more detail below with            respect to FIGS. 5A-5C. According to the invention,            noticeable spikes into/toward the lower bands of FIG. 2A (F            values relatively close to 0) can be construed as indicators            that a surface modification iteration has not proceeded            according to plan, as will now be elucidated in greater            detail.

FIG. 2B shows a nominal image of an exposed surface of the mouse brainspecimen used in generating FIG. 2A; this is an example of how thespecimen is “supposed to” look after a satisfactorily executed surfacemodification iteration, and it will be used as a reference/standard forthe discussion below.

-   -   Turning back to FIG. 2A, this shows two deep spikes onto the        boundary of the lowermost F-value band (0-0.1), namely one at        index 48 and one at index 83 (both of which occur in the        measurement set with d_(S)=20 nm). According to the invention,        such low F-values (proximal to zero) can be interpreted as an        indicator that a surface modification iteration has corrupted        the surface of the specimen, and this interpretation is        corroborated by FIGS. 3A and 3B, which show        post-surface-modification specimen images respectively        corresponding to these two indices (I 48 in FIG. 3A; 183 in FIG.        3B). These Figures clearly show the presence of debris on the        specimen surface—most likely in the form of a thin flake of        specimen that has fallen onto the freshly exposed surface after        a thinning step.    -   Also present in FIG. 2A are two spikes that extend as far as the        boundary of the third-lowest F-value band (0.2-0.3)—one        occurring around I 64 (d_(S)=20 nm) and the other occurring        around I 80 (d_(S)=10 nm).        -   Starting with the second of these, FIGS. 4A and 4B show            specimen images at indices I 79 and I 80, respectively, and            FIG. 4C shows a “difference image” obtained by subtracting            one image from the other. Careful inspection of FIG. 4B            reveals a discontinuity in the form of a sudden intra-image            lateral shift (about ⅖ of the way up from the bottom of the            image)—probably caused by a sudden jump in beam/stage scan            position during image acquisition. The difference image in            FIG. 4C reveals this shift more clearly, together with two            other such shifts—which seem to occur (quasi-)periodically            (from bottom to top of the image). As a result of these            shifts, the F-value is significantly reduced (F-0.3). Such            F-value behavior can be interpreted as a flag that there is            a problem (in this case, a scanning error), and that a            system check might be a worthwhile undertaking.        -   FIGS. 5A and 5B show specimen images at indices I 63 and I            64, respectively, and FIG. 5C shows a “difference image”            obtained by subtracting one image from the other. Careful            inspection of FIG. 5B (by a trained eye) indicates the            presence of image distortion (probably caused by lens            aberrations), principally near the upper and lower edges.            The difference image in FIG. 5C reveals this distortion more            clearly, with a relatively featureless “plain” across the            middle of the image, but with pronounced “topography” along            its upper and lower edges. As a result of this distortion,            the F-value is significantly reduced (F-0.3). Once again,            such F-value behavior can be interpreted as a flag that            there is a problem (in this case, an aberration issue), and            that a system check would be prudent.

The invention claimed is:
 1. A method of investigating a specimen usinga charged-particle microscope comprising: a specimen holder, for holdingthe specimen; a source, for producing a beam of charged-particleradiation; an illuminator, for directing said beam so as to irradiate asurface of the specimen; an imaging detector, for receiving a flux ofradiation emanating from the specimen in response to said irradiation,so as to produce an image of at least part of said surface; and anapparatus for modifying said surface by performing thereon a processselected from the group consisting of material removal, materialdeposition, and combinations thereof, wherein the apparatus has a set ofoperating parameters; the method comprising: defining a lower thresholdand an upper threshold for comparison with a primary figure of merit;producing and storing a first image, of a first, initial surface of thespecimen; setting the operating parameters for the apparatus; modifyingsaid first surface in a primary modification step by invoking saidapparatus, thereby yielding a second, modified surface; producing andstoring a second image, of said second surface; performing a pixel-wisecomparison of said first and second images using a mathematical imagesimilarity metric so as to generate the primary figure of merit for saidprimary modification step, wherein the primary figure of meritquantifies the similarity of the first and second images, and wherein achanging primary figure of merit indicates a changing similarity of thefirst and second images; and comparing the primary figure of merit tothe lower and upper thresholds, wherein if the primary figure of meritis above the upper threshold indicating a first outcome of the primarymodification step as indicated by the similarity of the first and secondimages, performing a first surface modification operation, and whereinif the primary figure of merit is below the lower threshold indicatingan outcome of the primary modification step different from the firstoutcome as indicated by the similarity of the first and second images,performing a second surface modification operation, different from thefirst surface modification operation.
 2. The method according to claim1, wherein said primary figure of merit is used to adjudge at least oneof the following scenarios: said primary modification step failed tomodify said first surface; said primary modification step insufficientlymodified said first surface; and said second surface is corruptedrelative to said first surface.
 3. The method according to claim 1,wherein, in a subsequent iteration, said primary figure of merit is usedto adjust at least one parameter of a secondary modification step,performed on said second surface.
 4. The method according to claim 1,wherein said primary figure of merit is used to quantify a thicknesschange produced in said specimen by said primary modification step. 5.The method according to claim 1, wherein said image similarity metric isselected from the group consisting of SSIM, MSE, PSNR, MIR, hybridsthereof, and combinations thereof.
 6. The method according to claim 1,wherein said apparatus is selected from the group consisting of amechanical cutting tool, a focused particle beam milling tool, anetching apparatus, a beam-induced deposition tool, a physical vapordeposition apparatus, a chemical vapor deposition apparatus, andcombinations thereof.
 7. The method according to claim 1, wherein saidapparatus is located in situ in said charged-particle microscope.
 8. Acharged-particle microscope comprising: a specimen holder, for holding aspecimen, wherein the specimen has a surface to be processed; a source,for producing a beam of charged-particle radiation; an illuminator, fordirecting said beam so as to irradiate the surface of the specimen; animaging detector, for receiving a flux of radiation emanating from thespecimen in response to said irradiation, so as to produce an image ofat least part of said surface; an apparatus for modifying the surface byperforming thereon a process selected from the group consisting ofmaterial removal, material deposition, and combinations thereof, whereinthe apparatus has a set of operating parameters; and an electronicprocessor that is programmed to: control, and adjust the operatingparameters of, the apparatus; acquire a first image from the specimen;modify the surface of the specimen in a primary modification step usingthe apparatus and then acquire a second image from the specimen; use amathematical image similarity metric to perform pixel-wise comparison offirst and second images to generate a numerical figure of merit thatquantifies the similarity of the first and second images, wherein achange in value of the numerical figure of merit would indicate a changein similarity of the first and second images; compare the numericalfigure of merit to an upper threshold and perform a first surfacemodification operation if the numerical figure of merit is above theupper threshold indicating a first outcome of the primary modificationstep as indicated by the similarity of the first and second images; andcompare the numerical figure of merit to a lower threshold and, if thenumerical figure of merit is below the lower threshold indicating anoutcome of the primary modification step different from the firstoutcome as indicated by the similarity of the first and second images,perform a second surface modification operation, different from thefirst surface modification operation.
 9. The charged particle microscopeaccording to claim 8, wherein said processor is programmed to; compilesaid first image prior to said primary modification step; compile saidsecond image after the primary modification step; and use said numericalfigure of merit to assign a success rating to the primary modificationstep.
 10. The charged particle microscope of claim 9, wherein saidnumerical figure of merit is selected from the group consisting of SSIM,MSE, PSNR, MIR, hybrids thereof, and combinations thereof.
 11. Thecharged particle microscope of claim 10, wherein said numerical figureof merit is used to quantify a thickness change produced in saidspecimen by said primary modification step.
 12. The method according toclaim 2, wherein, in a subsequent iteration, said primary figure ofmerit is used to adjust at least one parameter of a secondarymodification step, performed on said second surface.
 13. The methodaccording to claim 12, wherein said primary figure of merit is used toquantify a thickness change produced in said specimen by said primarymodification step.
 14. The method according to claim 2, wherein saidprimary figure of merit is used to quantify a thickness change producedin said specimen by said primary modification step.
 15. The methodaccording to claim 2, wherein said apparatus is selected from the groupconsisting of a mechanical cutting tool, a focused particle beam millingtool, an etching apparatus, a beam-induced deposition tool, a physicalvapor deposition apparatus, a chemical vapor deposition apparatus, andcombinations thereof.
 16. The method according to claim 1, furthercomprising repeating the modifying the surface of the specimen using theapparatus, the using a mathematical image similarity metric, and thecomparing the primary figure of merit to a lower threshold and to anupper threshold.
 17. The method according to claim 1, wherein in theperforming a pixel-wise comparison of said first and second images usinga mathematical image similarity metric so as to generate the primaryfigure of merit for said primary modification step, an increasingprimary figure of merit indicates an increasing similarity of the firstand second images.
 18. The method according to claim 17, wherein in thecomparing the primary figure of merit to the lower and upper thresholds,the first operation comprises repeating the setting the operatingparameters for the apparatus, and the second operation comprisescleaning or reconditioning the surface of the specimen.
 19. The chargedparticle microscope according to claim 8, wherein in the use of amathematical image similarity metric to perform pixel-wise comparison offirst and second images to generate a numerical figure of merit, anincreasing numerical figure of merit indicates an increasing similarityof the first and second images.
 20. The charged particle microscopeaccording to claim 19, wherein in the comparison of the numerical figureof merit to a lower threshold and to an upper threshold, the firstoperation comprises repeating the setting the operating parameters forthe apparatus, and the second operation comprises cleaning orreconditioning the surface of the specimen.